Scour assessment for offshore wind turbines: a state-of-the-art review

Xin Feng, Jintong Zheng, Yiming Liu, Yi Bao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Offshore wind turbines (OWTs) are subject to waves, currents, seabed shifts, and corrosion in harsh marine environment, posing significant challenges to structural integrity and durability. A prevalent issue of OWTs is the scour of foundations and cables, which can cause structural damage, interrupting the operation of OWTs and even leading to catastrophic failure. Timely detection and assessment of scour are crucial for maintaining the structural integrity and managing the operation of OWTs. This paper reviews the main methods utilized to assess scour for OWT. Three main types of scour assessment methods are reviewed, which are direct methods, vibration-based methods, and unmanned vehicle-based methods. For each type of methods, the reviewed contents mainly include the assessment principles, laboratory tests, and field applications, as well as data processing and interpretation. The limitations of existing methods and the new opportunities are discussed. This research promotes improvement of the monitoring and maintenance of OWTs.

Original languageEnglish
Article number112250
JournalJournal of Civil Structural Health Monitoring
DOIs
StateAccepted/In press - 2025

Keywords

  • Digital twin
  • Machine learning
  • Offshore wind turbine (OWT)
  • Scour
  • Structural health monitoring (SHM)
  • Unmanned vehicle

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